A Top-Down Cortical Circuit for Accurate Sensory Perception

Top-down control: A unified principle of cortical learning

Cognitive control of the brain flexibly maps incoming sensory information onto execution of actions appropriate for the current goal. Learning is a process that enables the brain to estimate current states of the world by extracting its spatiotemporal structure and generate goal-directed motor outputs through selective association of events or movement refinement. Accumulating evidence suggests that top-down control from higher-order brain areas modulates downstream neural activity and changes local computations that are critical for the execution of learned behavior. Recent technological advances in multi-site recordings and optogenetic approaches are beginning to reveal more direct evidence of top-down cognitive control by monitoring and perturbing activity of top-down inputs and observing its causal consequences on behavior and downstream neural dynamics. Here I highlight that learning-related changes in neural circuits in distinct domains of learning converge onto a unified principle; namely recruitment of top-down control whether it involves sensory, motor or offline learning. Recruitment of top-down control may reflect experience-dependent adaptation and integration of internal models for refined state estimation and goal-directed optimal behavior.

Circuit architecture for somatotopic action selection in invertebrates

Invertebrate species have significantly contributed to neuroscience owing to the accessibility they provide to cellular- and molecular-level understanding of brain functions. Somatotopic action selection is one of the key features of animal behavior, and studying this process in invertebrates is potentially a sweet spot in understanding the general relationship between neuronal morphology, circuit structure, and animal behavior. In this review, we introduce circuit architectures that realize somatotopic action selection, from simple reflexes to patterned motor outputs, in different invertebrate species. We then discuss future directions towards understanding the general principles underlying the development and evolution of the circuit architecture that enables sensorimotor transformation and action selection in the animal kingdom.

Cortical signatures of wakeful somatosensory processing

Sensory inputs carry critical information for the survival of an organism. In mice, tactile information conveyed by the whiskers is of high behavioural relevance, and is broadcasted across cortical areas beyond the primary somatosensory cortex. Mesoscopic voltage sensitive dye imaging (VSDI) of cortical population response to whisker stimulations has shown that seemingly 'simple' sensory stimuli can have extended impact on cortical circuit dynamics. Here we took advantage of genetically encoded voltage indicators (GEVIs) that allow for cell type-specific monitoring of population voltage dynamics in a chronic dual-hemisphere transcranial windowed mouse preparation to directly compare the cortex-wide broadcasting of sensory information in wakening (lightly anesthetized to sedated) and awake mice. Somatosensory-evoked cortex-wide dynamics is altered across brain states, with anatomically sequential hyperpolarising activity observed in the awake cortex. GEVI imaging revealed cortical activity maps with increased specificity, high spatial coverage, and at the timescale of cortical information processing.

Behavioral Strategy Determines Frontal or Posterior Location of Short-Term Memory in Neocortex

The location of short-term memory in mammalian neocortex remains elusive. Here we show that distinct neocortical areas maintain short-term memory depending on behavioral strategy. Using wide-field and single-cell calcium imaging, we measured layer 2/3 neuronal activity in mice performing a whisker-based texture discrimination task with delayed response. Mice either deployed an active strategy-engaging their body toward the approaching texture-or passively awaited the touch. Independent of strategy, whisker-related posterior areas encoded choice early after touch. During the delay, in contrast, persistent cortical activity was located medio-frontally in active trials but in a lateral posterior area in passive trials. Perturbing these areas impaired performance for the associated strategy and also provoked strategy switches. Frontally maintained information related to future action, whereas activity in the posterior cortex reflected past stimulus identity. Thus, depending on behavioral strategy, cortical activity is routed differentially to hold information either frontally or posteriorly before converging to similar action.

A Perspective on Cortical Layering and Layer-Spanning Neuronal Elements

This review article addresses the function of the layers of the cerebral cortex. We develop the perspective that cortical layering needs to be understood in terms of its functional anatomy, i.e., the terminations of synaptic inputs on distinct cellular compartments and their effect on cortical activity. The cortex is a hierarchical structure in which feed forward and feedback pathways have a layer-specific termination pattern. We take the view that the influence of synaptic inputs arriving at different cortical layers can only be understood in terms of their complex interaction with cellular biophysics and the subsequent computation that occurs at the cellular level. We use high-resolution fMRI, which can resolve activity across layers, as a case study for implementing this approach by describing how cognitive events arising from the laminar distribution of inputs can be interpreted by taking into account the properties of neurons that span different layers. This perspective is based on recent advances in measuring subcellular activity in distinct feed-forward and feedback axons and in dendrites as they span across layers.

Robust tactile sensory responses in finger area of primate motor cortex relevant to prosthetic control

OBJECTIVE

Challenges in improving the performance of dexterous upper-limb brain-machine interfaces (BMIs) have prompted renewed interest in quantifying the amount and type of sensory information naturally encoded in the primary motor cortex (M1). Previous single unit studies in monkeys showed M1 is responsive to tactile stimulation, as well as passive and active movement of the limbs. However, recent work in this area has focused primarily on proprioception. Here we examined instead how tactile somatosensation of the hand and fingers is represented in M1.

APPROACH

We recorded multi- and single units and thresholded neural activity from macaque M1 while gently brushing individual finger pads at 2 Hz. We also recorded broadband neural activity from electrocorticogram (ECoG) grids placed on human motor cortex, while applying the same tactile stimulus.

MAIN RESULTS

Units displaying significant differences in firing rates between individual fingers (p  <  0.05) represented up to 76.7% of sorted multiunits across four monkeys. After normalizing by the number of channels with significant motor finger responses, the percentage of electrodes with significant tactile responses was 74.9%  ±  24.7%. No somatotopic organization of finger preference was obvious across cortex, but many units exhibited cosine-like tuning across multiple digits. Sufficient sensory information was present in M1 to correctly decode stimulus position from multiunit activity above chance levels in all monkeys, and also from ECoG gamma power in two human subjects.

SIGNIFICANCE

These results provide some explanation for difficulties experienced by motor decoders in clinical trials of cortically controlled prosthetic hands, as well as the general problem of disentangling motor and sensory signals in primate motor cortex during dextrous tasks. Additionally, examination of unit tuning during tactile and proprioceptive inputs indicates cells are often tuned differently in different contexts, reinforcing the need for continued refinement of BMI training and decoding approaches to closed-loop BMI systems for dexterous grasping.

Apical Function in Neocortical Pyramidal Cells: A Common Pathway by Which General Anesthetics Can Affect Mental State

It has been argued that general anesthetics suppress the level of consciousness, or the contents of consciousness, or both. The distinction between level and content is important because, in addition to clarifying the mechanisms of anesthesia, it may help clarify the neural bases of consciousness. We assess these arguments in the light of evidence that both the level and the content of consciousness depend upon the contribution of apical input to the information processing capabilities of neocortical pyramidal cells which selectively amplify relevant signals. We summarize research suggesting that what neocortical pyramidal cells transmit information about can be distinguished from levels of arousal controlled by sub-cortical nuclei and from levels of prioritization specified by interactions within the thalamocortical system. Put simply, on the basis of the observations reviewed, we hypothesize that when conscious we have particular, directly experienced, percepts, thoughts, feelings and intentions, and that general anesthetics affect consciousness by interfering with the subcellular processes by which particular activities are selectively amplified when relevant to the current context.

Redundancy in synaptic connections enables neurons to learn optimally

Recent experimental studies suggest that, in cortical microcircuits of the mammalian brain, the majority of neuron-to-neuron connections are realized by multiple synapses. However, it is not known whether such redundant synaptic connections provide any functional benefit. Here, we show that redundant synaptic connections enable near-optimal learning in cooperation with synaptic rewiring. By constructing a simple dendritic neuron model, we demonstrate that with multisynaptic connections synaptic plasticity approximates a sample-based Bayesian filtering algorithm known as particle filtering, and wiring plasticity implements its resampling process. Extending the proposed framework to a detailed single-neuron model of perceptual learning in the primary visual cortex, we show that the model accounts for many experimental observations. In particular, the proposed model reproduces the dendritic position dependence of spike-timing-dependent plasticity and the functional synaptic organization on the dendritic tree based on the stimulus selectivity of presynaptic neurons. Our study provides a conceptual framework for synaptic plasticity and rewiring.

Learning Task-Related Activities From Independent Local-Field-Potential Components Across Motor Cortex Layers

Motor cortical microcircuits receive inputs from dispersed cortical and subcortical regions in behaving animals. However, how these inputs contribute to learning and execution of voluntary sequential motor behaviors remains elusive. Here, we analyzed the independent components extracted from the local field potential (LFP) activity recorded at multiple depths of rat motor cortex during reward-motivated movement to study their roles in motor learning. Because slow gamma (30-50 Hz), fast gamma (60-120 Hz), and theta (4-10 Hz) oscillations temporally coordinate task-relevant motor cortical activities, we first explored the behavioral state- and layer-dependent coordination of motor behavior in these frequency ranges. Consistent with previous findings, oscillations in the slow and fast gamma bands dominated during distinct movement states, i.e., preparation and execution states, respectively. However, we identified a novel independent component that dominantly appeared in deep cortical layers and exhibited enhanced slow gamma activity during the execution state. Then, we used the four major independent components to train a recurrent network model for the same lever movements as the rats performed. We show that the independent components differently contribute to the formation of various task-related activities, but they also play overlapping roles in motor learning.

Median nerve stimulation induced motor learning in healthy adults: A study of timing of stimulation and type of learning

Median nerve stimulation (MNS) has been shown to change brain metaplasticity over the somatosensory networks, based on a bottom-up mechanism and may improve motor learning. This exploratory study aimed to test the effects of MNS on implicit and explicit motor learning as measured by the serial reaction time task (SRTT) using a double-blind, sham-controlled, randomized trial, in which participants were allocated to one of three groups: (a) online active MNS during acquisition, (b) offline active MNS during early consolidation and (c) sham MNS. SRTT was performed at baseline, during the training phase (acquisition period), and 30 min after training. We assessed the effects of MNS on explicit and implicit motor learning at the end of the training/acquisition period and at retest. The group receiving online MNS (during acquisition) showed a significantly higher learning index for the explicit sequences compared to the offline group (MNS during early consolidation) and the sham group. The offline group also showed a higher learning index as compared to sham. Additionally, participants receiving online MNS recalled the explicit sentence significantly more than the offline MNS and sham groups. MNS effects on motor learning have a specific effect on type of learning (explicit vs. implicit) and are dependent on timing of stimulation (during acquisition vs. early consolidation). More research is needed to understand and optimize the effects of peripheral electrical stimulation on motor learning. Taken together, our results show that MNS, especially when applied during the acquisition phase, is a promising tool to modulate motor leaning.

Serotonin Selectively Increases Detectability of Motion Stimuli in the Electrosensory System

Serotonergic innervation of sensory areas is found ubiquitously across the central nervous system of vertebrates. Here, we used a system's level approach to investigate the role of serotonin on processing motion stimuli in the electrosensory system of the weakly electric fish Apteronotus albifrons. We found that exogenous serotonin application increased the firing activity of pyramidal neural responses to both looming and receding motion. Separating spikes belonging to bursts from those that were isolated revealed that this effect was primarily due to increased burst firing. Moreover, when investigating whether firing activity during stimulation could be discriminated from baseline (i.e., in the absence of stimulation), we found that serotonin increased stimulus discriminability only for some stimuli. This is because increased burst firing was most prominent for these. Further, the effects of serotonin were highly heterogeneous, with some neurons displaying large while others instead displaying minimal changes in responsiveness following serotonin application. Further analysis revealed that serotonin application had the greatest effect on neurons with low baseline firing rates and little to no effect on neurons with high baseline firing rates. Finally, the effects of serotonin on sensory neuron responses were largely independent of object velocity. Our results therefore reveal a novel function for the serotonergic system in selectively enhancing discriminability for motion stimuli.

Bottom-up and top-down modulation of multisensory integration

Sensory perception in the real world requires proper integration of different modality inputs. Process of multisensory integration is not uniform. It varies from individual to individual and changes at different behavioral states of the animal. What factors affect multisensory integration? How does the mammalian brain reconstruct a multisensory world at different states? Here, we summarize recent findings on bottom-up and top-down factors that can modulate sensory processing and multisensory integration. We discuss cortical circuits that are responsible for modulation of multisensory processing based on recent rodent studies. We suggest that multisensory information is not a simple, fixed signal in the brain. Multisensory processing is dynamically modulated in the mammalian brain and leads to a unique and subjective experience of perception.

Scaling of Optogenetically Evoked Signaling in a Higher-Order Corticocortical Pathway in the Anesthetized Mouse

Quantitative analysis of corticocortical signaling is needed to understand and model information processing in cerebral networks. However, higher-order pathways, hodologically remote from sensory input, are not amenable to spatiotemporally precise activation by sensory stimuli. Here, we combined parametric channelrhodopsin-2 (ChR2) photostimulation with multi-unit electrophysiology to study corticocortical driving in a parietofrontal pathway from retrosplenial cortex (RSC) to posterior secondary motor cortex (M2) in mice in vivo. Ketamine anesthesia was used both to eliminate complex activity associated with the awake state and to enable stable recordings of responses over a wide range of stimulus parameters. Photostimulation of ChR2-expressing neurons in RSC, the upstream area, produced local activity that decayed quickly. This activity in turn drove downstream activity in M2 that arrived rapidly (5-10 ms latencies), and scaled in amplitude across a wide range of stimulus parameters as an approximately constant fraction (~0.1) of the upstream activity. A model-based analysis could explain the corticocortically driven activity with exponentially decaying kernels (~20 ms time constant) and small delay. Reverse (antidromic) driving was similarly robust. The results show that corticocortical signaling in this pathway drives downstream activity rapidly and scalably, in a mostly linear manner. These properties, identified in anesthetized mice and represented in a simple model, suggest a robust basis for supporting complex non-linear dynamic activity in corticocortical circuits in the awake state.

Corticospinal Circuits from the Sensory and Motor Cortices Differentially Regulate Skilled Movements through Distinct Spinal Interneurons

Little is known about the organizational and functional connectivity of the corticospinal (CS) circuits that are essential for voluntary movement. Here, we map the connectivity between CS neurons in the forelimb motor and sensory cortices and various spinal interneurons, demonstrating that distinct CS-interneuron circuits control specific aspects of skilled movements. CS fibers originating in the mouse motor cortex directly synapse onto premotor interneurons, including those expressing Chx10. Lesions of the motor cortex or silencing of spinal Chx10+ interneurons produces deficits in skilled reaching. In contrast, CS neurons in the sensory cortex do not synapse directly onto premotor interneurons, and they preferentially connect to Vglut3+ spinal interneurons. Lesions to the sensory cortex or inhibition of Vglut3+ interneurons cause deficits in food pellet release movements in goal-oriented tasks. These findings reveal that CS neurons in the motor and sensory cortices differentially control skilled movements through distinct CS-spinal interneuron circuits.

Effects of meaningfulness on perception: Alpha-band oscillations carry perceptual expectations and influence early visual responses

Perceptual experience results from a complex interplay of bottom-up input and prior knowledge about the world, yet the extent to which knowledge affects perception, the neural mechanisms underlying these effects, and the stages of processing at which these two sources of information converge, are still unclear. In several experiments we show that language, in the form of verbal labels, both aids recognition of ambiguous “Mooney” images and improves objective visual discrimination performance in a match/non-match task. We then used electroencephalography (EEG) to better understand the mechanisms of this effect. The improved discrimination of images previously labeled was accompanied by a larger occipital-parietal P1 evoked response to the meaningful versus meaningless target stimuli. Time-frequency analysis of the interval between the cue and the target stimulus revealed increases in the power of posterior alpha-band (8–14 Hz) oscillations when the meaning of the stimuli to be compared was trained. The magnitude of the pre-target alpha difference and the P1 amplitude difference were positively correlated across individuals. These results suggest that prior knowledge prepares the brain for upcoming perception via the modulation of alpha-band oscillations, and that this preparatory state influences early (~120 ms) stages of visual processing.

The functional organization of cortical feedback inputs to primary visual cortex

Cortical feedback is thought to mediate cognitive processes like attention, prediction, and awareness. Understanding its function requires identifying the organizational logic of feedback axons relaying different signals. We measured retinotopic specificity in inputs from the lateromedial visual area in mouse primary visual cortex (V1) by mapping receptive fields in feedback boutons and relating them to those of neurons in their vicinity. Lateromedial visual area inputs in layer 1 targeted, on average, retinotopically matched locations in V1, but many of them relayed distal visual information. Orientation-selective axons overspread around the retinotopically matched location perpendicularly to their preferred orientation. Direction-selective axons were biased to visual areas shifted from the retinotopically matched position along the angle of their antipreferred direction. Our results show that feedback inputs show tuning-dependent retinotopic specificity. By targeting locations that would be activated by stimuli orthogonal to or opposite to a cell's own tuning, feedback could potentially enhance visual representations in time and space.

Somatosensory electrical stimulation improves skill acquisition, consolidation, and transfer by increasing sensorimotor activity and connectivity

The interaction between the somatosensory and motor systems is important for normal human motor function and learning. Enhancing somatosensory input using somatosensory electrical stimulation (SES) can increase motor performance, but the neuronal mechanisms underlying these effects are largely unknown. With EEG, we examined whether skill acquisition, consolidation, and interlimb transfer after SES was related to increased activity in sensorimotor regions, as assessed by the N30 somatosensory evoked potential or rather increased connectivity between these regions, as assessed by the phase slope index (PSI). Right- and left-hand motor performance and EEG measures were taken before, immediately after, and 24 h ( day 2) after either SES ( n = 12; 5 men) or Control ( n = 12; 5 men). The results showed skill acquisition and consolidation in the stimulated right hand immediately after SES (6%) and on day 2 (9%) and interlimb transfer to the nonstimulated left hand on day 2 relative to Control (8%, all P < 0.05). Increases in N30 amplitudes correlated with skill acquisition while PSI from electrodes that represent the posterior parietal and primary somatosensory cortex to the electrode representing the primary motor cortex correlated with skill consolidation. In contrast, interlimb transfer did not correlate with the EEG-derived neurophysiological estimates obtained in the present study, which may indicate the involvement of subcortical structures in interlimb transfer after SES. In conclusion, weak peripheral somatosensory inputs in the form of SES improve skill acquisition, consolidation, and interlimb transfer that coincide with different cortical adaptations, including enhanced N30 amplitudes and PSI. NEW & NOTEWORTHY The relationship between adaptations in synaptic plasticity and motor learning following somatosensory electrical stimulation (SES) is incompletely understood. Here, we used for the first time a multifactorial approach that examined skill acquisition, consolidation, and interlimb transfer following 20 min of SES. In addition, we quantified sensorimotor integration and the magnitude and direction of connectivity with EEG. Following artificial electrical stimulation, increases in sensorimotor integration and connectivity were found to correlate with skill acquisition and consolidation, respectively.

Fast and accurate edge orientation processing during object manipulation

Quickly and accurately extracting information about a touched object’s orientation is a critical aspect of dexterous object manipulation. However, the speed and acuity of tactile edge orientation processing with respect to the fingertips as reported in previous perceptual studies appear inadequate in these respects. Here we directly establish the tactile system’s capacity to process edge-orientation information during dexterous manipulation. Participants extracted tactile information about edge orientation very quickly, using it within 200 ms of first touching the object. Participants were also strikingly accurate. With edges spanning the entire fingertip, edge-orientation resolution was better than 3° in our object manipulation task, which is several times better than reported in previous perceptual studies. Performance remained impressive even with edges as short as 2 mm, consistent with our ability to precisely manipulate very small objects. Taken together, our results radically redefine the spatial processing capacity of the tactile system.

Putting on a necklace requires using your fingertips to hold open a clasp, which you then insert into a small ring. For you to do this, your nervous system must first work out which way the clasp and the ring are facing relative to one another. It then uses that information to coordinate the movements of your fingertips. If you fasten the necklace behind your head, your nervous system must perform these tasks without information from your eyes. Instead, it must use the way in which the edges of the clasp and the ring indent the skin on your fingertips to work out their orientation.

Earlier studies have examined this process by asking healthy volunteers to judge the orientation of objects – or more precisely edges – that an experimenter has pressed against their fingertips. But people perform worse than expected on this task given their manual dexterity. Pruszynski et al. wondered whether the task might underestimate the abilities of the volunteers because it involves passively perceiving objects, rather than actively manipulating them.

To test this idea, Pruszynski et al. designed a new experiment. Healthy volunteers were asked to use a fingertip to rotate a pointer on a dial to a target location. The participants could not see the dial, and so they had to use touch alone to determine which way the pointer was facing. They performed the task faster and more accurately than volunteers in the earlier passive experiments. Indeed, when the pointer was longer than a fingertip, the volunteers performed almost as well using touch alone as when allowed to look at the dial. Speed and accuracy remained impressive even when the pointer was only 2mm long.

The results of Pruszynski et al. show that we judge orientation more accurately when we manipulate objects than when we passively perceive them. In other words, we do better when we perform tasks in which being aware of orientation is vital. The results also suggest that the nervous system processes sensory information in different ways when it uses sensations to help control objects as opposed to just perceiving them. This could influence the development of new technology that aims to use brain activity to control computers or robotic limbs.

Novel concepts in sleep regulation

Knowledge regarding the cellular mechanisms of sleep regulation is accumulating rapidly. In addition to neurones, also non-neuronal brain cells (astrocytes and microglia) are emerging as potential players. New techniques, particularly optogenetics and designed receptors activated by artificial ligands (DREADD), have provided also sleep research with important additional tools to study the effect of either silencing or activating specific neuronal groups/neuronal networks by opening or shutting ion channels on cells. The advantages of these strategies are the possibility to genetically target specific cell populations and the possibility to either activate or inhibit them with inducing light signal into the brain. Studies probing circuits of NREM and REM sleep regulation, as well as their role in memory consolidation, have been conducted recently. In addition, fundamentally new thoughts and potential mechanisms have been introduced to the field. The role of non-neuronal tissues in the regulation of many brain functions has become evident. These non-neuronal cells, particularly astrocytes, integrate large number of neurones, and it has been suggested that one of their functions is to integrate the (neural) activity in larger brain areas-a feature that is one of the prominent features of also the state of sleep.

Mapping GPR88-Venus illuminates a novel role for GPR88 in sensory processing

GPR88 is an orphan G-protein coupled receptor originally characterized as a striatal-enriched transcript and is a potential target for neuropsychiatric disorders. At present, gene knockout studies in the mouse have essentially focused on striatal-related functions and a comprehensive knowledge of GPR88 protein distribution and function in the brain is still lacking. Here, we first created Gpr88-Venus knock-in mice expressing a functional fluorescent receptor to fine-map GPR88 localization in the brain. The receptor protein was detected in neuronal soma, fibers and primary cilia depending on the brain region, and remarkably, whole-brain mapping revealed a yet unreported layer-4 cortical lamination pattern specifically in sensory processing areas. The unique GPR88 barrel pattern in L4 of the somatosensory cortex appeared 3 days after birth and persisted into adulthood, suggesting a potential function for GPR88 in sensory integration. We next examined Gpr88 knockout mice for cortical structure and behavioral responses in sensory tasks. Magnetic resonance imaging of live mice revealed abnormally high fractional anisotropy, predominant in somatosensory cortex and caudate putamen, indicating significant microstructural alterations in these GPR88-enriched areas. Further, behavioral analysis showed delayed responses in somatosensory-, visual- and olfactory-dependent tasks, demonstrating a role for GPR88 in the integration rather than perception of sensory stimuli. In conclusion, our data show for the first time a prominent role for GPR88 in multisensory processing. Because sensory integration is disrupted in many psychiatric diseases, our study definitely positions GPR88 as a target to treat mental disorders perhaps via activity on cortical sensory networks.

High-performance, inexpensive setup for simultaneous multisite recording of electrophysiological signals and mesoscale voltage imaging in the mouse cortex

Simultaneous recording of optical and electrophysiological signals from multiple cortical areas may provide crucial information to expand our understanding of cortical function. However, the insertion of multiple electrodes into the brain may compromise optical imaging by both restricting the field of view and interfering with the approaches used to stabilize the specimen. Existing methods that combine electrophysiological recording and optical imaging in vivo implement either multiple surface electrodes, silicon probes, or a single electrode for deeper recordings. To address such limitation, we built a microelectrode array (hyperdrive, patent US5928143 A) compatible with wide-field imaging that allows insertion of up to 12 probes into a large brain area (8 mm diameter). The hyperdrive is comprised of a circle of individual microdrives where probes are positioned at an angle leaving a large brain area unobstructed for wide-field imaging. Multiple tetrodes and voltage-sensitive dye imaging were used for acute simultaneous registration of spontaneous and evoked cortical activity in anesthetized mice. The electrophysiological signals were used to extract local field potential (LFP) traces, multiunit, and single-unit spiking activity. To demonstrate our approach, we compared LFP and VSD signals over multiple regions of the cortex and analyzed the relationship between single-unit and global cortical population activities. The study of the interactions between cortical activity at local and global scales, such as the one presented in this work, can help to expand our knowledge of brain function.

Perceptual judgments via sensory-motor interaction assisted by cortical GABA

Recurrent input to sensory cortex, via long-range reciprocal projections between motor and sensory cortices, is essential for accurate perceptual judgments. GABA levels in sensory cortices correlate with perceptual performance. We simulated a neuron-astrocyte network model to investigate how top-down, feedback signaling from a motor network (Nmot) to a sensory network (Nsen) affects perceptual judgments in association with ambient (extracellular) GABA levels. In the Nsen, astrocytic transporters modulated ambient GABA levels around pyramidal cells. A simple perceptual task was implemented: detection of a feature stimulus presented to the Nsen. The Nmot showed distinct perceptual behaviors: hit, fault, and miss. A hit is a correct response to the stimulus, a fault is a wrong response to the stimulus, and a miss is no response to the stimulus. In hits, the feedback signaling increased the gain of Nsen pyramidal cells and accelerated the reaction speed of Nmot pyramidal cells to the stimulus. Without feedback signaling, the Nsen but not Nmot responded to the stimulus, resulting in a miss. With too strong feedback signaling, the Nmot resulted in a fault, namely, stimulus-insensitive but not stimulus-sensitive pyramidal cells wrongly responded. Balancing the feedforward and feedback signaling formed a coherent, ongoing-spontaneous neuronal state, by which the highest hit rate was achieved. A transient reduction in local ambient GABA levels, triggered by the stimulus, contributed to accelerating the reaction speed under noisy environmental conditions. Adjusting the basal ambient GABA level ensured high hit rates. We suggest that motor cortex feedback may accelerate reaction speed to sensory stimulation by promoting coherency in ongoing-spontaneous neuronal activity between sensory and motor cortices, thereby achieving prompt perceptual judgments. Spatiotemporal modulation of ambient GABA levels, possibly by astrocytic transporters, assists in making reliable perceptual judgments.

Streamlined sensory motor communication through cortical reciprocal connectivity in a visually guided eye movement task

Cortical computation is distributed across multiple areas of the cortex by networks of reciprocal connectivity. However, how such connectivity contributes to the communication between the connected areas is not clear. In this study, we examine the communication between sensory and motor cortices. We develop an eye movement task in mice and combine it with optogenetic suppression and two-photon calcium imaging techniques. We identify a small region in the secondary motor cortex (MO_s) that controls eye movements and reciprocally connects with a rostrolateral part of the higher visual areas (V_RL/A/AL). These two regions encode both motor signals and visual information; however, the information flow between the regions depends on the direction of the connectivity: motor information is conveyed preferentially from the MO_s to the V_RL/A/AL, and sensory information is transferred primarily in the opposite direction. We propose that reciprocal connectivity streamlines information flow, enhancing the computational capacity of a distributed network.

Reciprocal connectivity enables tightly coupled information processing across cortical areas. Here the authors develop a visual oculomotor task in mice, identify a small motor area required for it, and demonstrate selective exchange of sensory and motor information between the motor and sensory areas.

Single-Cell Stimulation in Barrel Cortex Influences Psychophysical Detection Performance

A single whisker stimulus elicits action potentials in a sparse subset of neurons in somatosensory cortex. The precise contribution of these neurons to the animal's perception of a whisker stimulus is unknown. Here we show that single-cell stimulation in rat barrel cortex of both sexes influences the psychophysical detection of a near-threshold whisker stimulus in a cell type-dependent manner, without affecting false alarm rate. Counterintuitively, stimulation of single fast-spiking putative inhibitory neurons increased detection performance. Single-cell stimulation of putative excitatory neurons failed to change detection performance, except for a small subset of deep-layer neurons that were highly sensitive to whisker stimulation and that had an unexpectedly strong impact on detection performance. These findings indicate that the perceptual impact of excitatory barrel cortical neurons relates to their firing response to whisker stimulation and that strong activity in a single highly sensitive neuron in barrel cortex can already enhance sensory detection. Our data suggest that sensory detection is based on a decoding mechanism that lends a disproportionally large weight to interneurons and to deep-layer neurons showing a strong response to sensory stimulation.SIGNIFICANCE STATEMENT Rat whisker somatosensory cortex contains a variety of neuronal cell types with distinct anatomical and physiological characteristics. How each of these different cell types contribute to the animal's perception of whisker stimuli is unknown. We explored this question by using a powerful electrophysiological stimulation technique that allowed us to target and stimulate single neurons with different sensory response types in whisker cortex. In awake, behaving animals, trained to detect whisker stimulation, only costimulation of single fast-spiking inhibitory neurons or single deep-layer excitatory neurons with strong responses to whisker stimulation enhanced detection performance. Our data demonstrate that single cortical neurons can have measurable impact on the detection of sensory stimuli and suggest a decoding mechanism based on select cell types.

Neuronal Assemblies Evidence Distributed Interactions within a Tactile Discrimination Task in Rats

Accumulating evidence suggests that neural interactions are distributed and relate to animal behavior, but many open questions remain. The neural assembly hypothesis, formulated by Hebb, states that synchronously active single neurons may transiently organize into functional neural circuits-neuronal assemblies (NAs)-and that would constitute the fundamental unit of information processing in the brain. However, the formation, vanishing, and temporal evolution of NAs are not fully understood. In particular, characterizing NAs in multiple brain regions over the course of behavioral tasks is relevant to assess the highly distributed nature of brain processing. In the context of NA characterization, active tactile discrimination tasks with rats are elucidative because they engage several cortical areas in the processing of information that are otherwise masked in passive or anesthetized scenarios. In this work, we investigate the dynamic formation of NAs within and among four different cortical regions in long-range fronto-parieto-occipital networks (primary somatosensory, primary visual, prefrontal, and posterior parietal cortices), simultaneously recorded from seven rats engaged in an active tactile discrimination task. Our results first confirm that task-related neuronal firing rate dynamics in all four regions is significantly modulated. Notably, a support vector machine decoder reveals that neural populations contain more information about the tactile stimulus than the majority of single neurons alone. Then, over the course of the task, we identify the emergence and vanishing of NAs whose participating neurons are shown to contain more information about animal behavior than randomly chosen neurons. Taken together, our results further support the role of multiple and distributed neurons as the functional unit of information processing in the brain (NA hypothesis) and their link to active animal behavior.

The Sensory Neocortex and Associative Memory

Most behaviors in mammals are directly or indirectly guided by prior experience and therefore depend on the ability of our brains to form memories. The ability to form an association between an initially possibly neutral sensory stimulus and its behavioral relevance is essential for our ability to navigate in a changing environment. The formation of a memory is a complex process involving many areas of the brain. In this chapter we review classic and recent work that has shed light on the specific contribution of sensory cortical areas to the formation of associative memories. We discuss synaptic and circuit mechanisms that mediate plastic adaptations of functional properties in individual neurons as well as larger neuronal populations forming topographically organized representations. Furthermore, we describe commonly used behavioral paradigms that are used to study the mechanisms of memory formation. We focus on the auditory modality that is receiving increasing attention for the study of associative memory in rodent model systems. We argue that sensory cortical areas may play an important role for the memory-dependent categorical recognition of previously encountered sensory stimuli.

Reward-Based Learning Drives Rapid Sensory Signals in Medial Prefrontal Cortex and Dorsal Hippocampus Necessary for Goal-Directed Behavior

The neural circuits underlying learning and execution of goal-directed behaviors remain to be determined. Here, through electrophysiological recordings, we investigated fast sensory processing across multiple cortical areas as mice learned to lick a reward spout in response to a brief deflection of a single whisker. Sensory-evoked signals were absent from medial prefrontal cortex and dorsal hippocampus in naive mice, but developed with task learning and correlated with behavioral performance in mice trained in the detection task. The sensory responses in medial prefrontal cortex and dorsal hippocampus occurred with short latencies of less than 50 ms after whisker deflection. Pharmacological and optogenetic inactivation of medial prefrontal cortex or dorsal hippocampus impaired behavioral performance. Neuronal activity in medial prefrontal cortex and dorsal hippocampus thus appears to contribute directly to task performance, perhaps providing top-down control of learned, context-dependent transformation of sensory input into goal-directed motor output.

Towards deep learning with segregated dendrites

Deep learning has led to significant advances in artificial intelligence, in part, by adopting strategies motivated by neurophysiology. However, it is unclear whether deep learning could occur in the real brain. Here, we show that a deep learning algorithm that utilizes multi-compartment neurons might help us to understand how the neocortex optimizes cost functions. Like neocortical pyramidal neurons, neurons in our model receive sensory information and higher-order feedback in electrotonically segregated compartments. Thanks to this segregation, neurons in different layers of the network can coordinate synaptic weight updates. As a result, the network learns to categorize images better than a single layer network. Furthermore, we show that our algorithm takes advantage of multilayer architectures to identify useful higher-order representations—the hallmark of deep learning. This work demonstrates that deep learning can be achieved using segregated dendritic compartments, which may help to explain the morphology of neocortical pyramidal neurons.

Artificial intelligence has made major progress in recent years thanks to a technique known as deep learning, which works by mimicking the human brain. When computers employ deep learning, they learn by using networks made up of many layers of simulated neurons. Deep learning has opened the door to computers with human – or even super-human – levels of skill in recognizing images, processing speech and controlling vehicles. But many neuroscientists are skeptical about whether the brain itself performs deep learning.

The patterns of activity that occur in computer networks during deep learning resemble those seen in human brains. But some features of deep learning seem incompatible with how the brain works. Moreover, neurons in artificial networks are much simpler than our own neurons. For instance, in the region of the brain responsible for thinking and planning, most neurons have complex tree-like shapes. Each cell has ‘roots’ deep inside the brain and ‘branches’ close to the surface. By contrast, simulated neurons have a uniform structure.

To find out whether networks made up of more realistic simulated neurons could be used to make deep learning more biologically realistic, Guerguiev et al. designed artificial neurons with two compartments, similar to the ‘roots’ and ‘branches’. The network learned to recognize hand-written digits more easily when it had many layers than when it had only a few. This shows that artificial neurons more like those in the brain can enable deep learning. It even suggests that our own neurons may have evolved their shape to support this process.

If confirmed, the link between neuronal shape and deep learning could help us develop better brain-computer interfaces. These allow people to use their brain activity to control devices such as artificial limbs. Despite advances in computing, we are still superior to computers when it comes to learning. Understanding how our own brains show deep learning could thus help us develop better, more human-like artificial intelligence in the future.

The Roles of Cortical Slow Waves in Synaptic Plasticity and Memory Consolidation

Sleep plays important roles in sensory and motor memory consolidation. Sleep oscillations, reflecting neural population activity, involve the reactivation of learning-related neurons and regulate synaptic strength and, thereby affect memory consolidation. Among sleep oscillations, slow waves (0.5–4 Hz) are closely associated with memory consolidation. For example, slow-wave power is regulated in an experience-dependent manner and correlates with acquired memory. Furthermore, manipulating slow waves can enhance or impair memory consolidation. During slow wave sleep, inter-areal interactions between the cortex and hippocampus (HC) have been proposed to consolidate declarative memory; however, interactions for non-declarative (HC-independent) memory remain largely uninvestigated. We recently showed that the directional influence in a slow-wave range through a top-down cortical long-range circuit is involved in the consolidation of non-declarative memory. At the synaptic level, the average cortical synaptic strength is known to be potentiated during wakefulness and depressed during sleep. Moreover, learning causes plasticity in a subset of synapses, allocating memory to them. Sleep may help to differentiate synaptic strength between allocated and non-allocated synapses (i.e., improving the signal-to-noise ratio, which may facilitate memory consolidation). Herein, we offer perspectives on inter-areal interactions and synaptic plasticity for memory consolidation during sleep.

Consciousness Regained: Disentangling Mechanisms, Brain Systems, and Behavioral Responses

How consciousness (experience) arises from and relates to material brain processes (the "mind-body problem") has been pondered by thinkers for centuries, and is regarded as among the deepest unsolved problems in science, with wide-ranging theoretical, clinical, and ethical implications. Until the last few decades, this was largely seen as a philosophical topic, but not widely accepted in mainstream neuroscience. Since the 1980s, however, novel methods and theoretical advances have yielded remarkable results, opening up the field for scientific and clinical progress. Since a seminal paper by Crick and Koch (1998) claimed that a science of consciousness should first search for its neural correlates (NCC), a variety of correlates have been suggested, including both content-specific NCCs, determining particular phenomenal components within an experience, and the full NCC, the neural substrates supporting entire conscious experiences. In this review, we present recent progress on theoretical, experimental, and clinical issues. Specifically, we (1) review methodological advances that are important for dissociating conscious experience from related enabling and executive functions, (2) suggest how critically reconsidering the role of the frontal cortex may further delineate NCCs, (3) advocate the need for general, objective, brain-based measures of the capacity for consciousness that are independent of sensory processing and executive functions, and (4) show how animal studies can reveal population and network phenomena of relevance for understanding mechanisms of consciousness.

Systematic population spike delays across cortical layers within and between primary sensory areas

The coordinated propagation of activity across cortical layers enables simultaneous local computation and inter-areal interactions. A pattern of upward propagation from deeper to more superficial layers, which has been repeatedly demonstrated in spontaneous activity, would allow these functions to occur in parallel. But it remains unclear whether upward propagation also occurs for stimulus evoked activity, and how it relates to activity in other cortical areas. Here we used a new method to analyze relative delays between spikes obtained from simultaneous laminar recordings in primary sensory cortex (S1) of both hemispheres. The results identified systematic spike delays across cortical layers that showed a general upward propagation of activity in evoked and spontaneous activity. Systematic spike delays were also observed between hemispheres. After spikes in one S1 the delays in the other S1 were shortest at infragranular layers and increased in the upward direction. Model comparisons furthermore showed that upward propagation was better explained as a step-wise progression over cortical layers than as a traveling wave. The results are in line with the notion that upward propagation functionally integrates activity into local processing at superficial layers, while efficiently allowing for simultaneous inter-areal interactions.

An Elegant Circuit for Balancing Risk and Reward

Animals constantly encounter conflicting cues in natural environments. To survive and thrive, they must make appropriate behavioral decisions. In this issue, Ghosh et al. (2016) identified a neural circuit underlying multisensory threat-reward decision making using an elegant C. elegans model.

Cortical dendritic activity correlates with spindle-rich oscillations during sleep in rodents

How sleep influences brain plasticity is not known. In particular, why certain electroencephalographic (EEG) rhythms are linked to memory consolidation is poorly understood. Calcium activity in dendrites is known to be necessary for structural plasticity changes, but this has never been carefully examined during sleep. Here, we report that calcium activity in populations of neocortical dendrites is increased and synchronised during oscillations in the spindle range in naturally sleeping rodents. Remarkably, the same relationship is not found in cell bodies of the same neurons and throughout the cortical column. Spindles during sleep have been suggested to be important for brain development and plasticity. Our results provide evidence for a physiological link of spindles in the cortex specific to dendrites, the main site of synaptic plasticity.

Different stages of sleep, marked by particular electroencephalographic (EEG) signatures, have been linked to memory consolidation, but underlying mechanisms are poorly understood. Here, the authors show that dendritic calcium synchronisation correlates with spindle-rich sleep phases.

Neocortical dynamics during whisker-based sensory discrimination in head-restrained mice

A fundamental task frequently encountered by brains is to rapidly and reliably discriminate between sensory stimuli of the same modality, be it distinct auditory sounds, odors, visual patterns, or tactile textures. A key mammalian brain structure involved in discrimination behavior is the neocortex. Sensory processing not only involves the respective primary sensory area, which is crucial for perceptual detection, but additionally relies on cortico-cortical communication among several regions including higher-order sensory areas as well as frontal cortical areas. It remains elusive how these regions exchange information to process neural representations of distinct stimuli to bring about a decision and initiate appropriate behavioral responses. Likewise, it is poorly understood how these neural computations are conjured during task learning. In this review, we discuss recent studies investigating cortical dynamics during discrimination behaviors that utilize head-fixed behavioral tasks in combination with in vivo electrophysiology, two-photon calcium imaging, and cell-type-specific targeting. We particularly focus on information flow in distinct cortico-cortical pathways when mice use their whiskers to discriminate between different objects or different locations. Within the primary and secondary somatosensory cortices (S1 and S2, respectively) as well as vibrissae motor cortex (M1), intermingled functional representations of touch, whisking, and licking were found, which partially re-organized during discrimination learning. These findings provide first glimpses of cortico-cortical communication but emphasize that for understanding the complete process of discrimination it will be crucial to elucidate the details of how neural processing is coordinated across brain-wide neuronal networks including the S1-S2-M1 triangle and cortical areas beyond.

Fast varifocal two-photon microendoscope for imaging neuronal activity in the deep brain

Fluorescence microendoscopy is becoming a promising approach for deep brain imaging, but the current technology for visualizing neurons on a single focal plane limits the experimental efficiency and the pursuit of three-dimensional functional neural circuit architectures. Here we present a novel fast varifocal two-photon microendoscope system equipped with a gradient refractive index (GRIN) lens and an electrically tunable lens (ETL). This microendoscope enables quasi-simultaneous imaging of the neuronal network activity of deep brain areas at multiple focal planes separated by 85-120 µm at a fast scan rate of 7.5-15 frames per second per plane, as demonstrated in calcium imaging of the mouse dorsal CA1 hippocampus and amygdala in vivo.

Dendritic calcium spikes are clearly detectable at the cortical surface

Cortical surface recording techniques such as EEG and ECoG are widely used for measuring brain activity. The prevailing assumption is that surface potentials primarily reflect synaptic activity, although non-synaptic events may also contribute. Here we show that dendritic calcium spikes occurring in pyramidal neurons (that we showed previously are cognitively relevant) are clearly detectable in cortical surface potentials. To show this we developed an optogenetic, non-synaptic approach to evoke dendritic calcium spikes in vivo. We found that optogenetically evoked calcium spikes were easily detectable and had an unexpected waveform near the cortical surface. Sensory-evoked dendritic calcium spikes were also clearly detectable with amplitudes that matched the contribution of synaptic input. These results reveal how dendritic calcium spikes appear at the cortical surface and their significant impact on surface potentials, suggesting that long-standing surface recording data may contain information about dendritic activity that is relevant to behavior and cognitive function.

Surface EEG recordings are thought to primarily detect synaptic activity. Here the authors devise an optogenetic method to evoke dendritic calcium spikes in layer 5 pyramidal cells of the rat somatosensory cortex, and report that optogenetically evoked, as well as sensory-evoked dendritic calcium spikes make a significant contribution to surface EEG recordings.

Circuit Mechanisms of Sensorimotor Learning

The relationship between the brain and the environment is flexible, forming the foundation for our ability to learn. Here we review the current state of our understanding of the modifications in the sensorimotor pathway related to sensorimotor learning. We divide the process into three hierarchical levels with distinct goals: (1) sensory perceptual learning, (2) sensorimotor associative learning, and (3) motor skill learning. Perceptual learning optimizes the representations of important sensory stimuli. Associative learning and the initial phase of motor skill learning are ensured by feedback-based mechanisms that permit trial-and-error learning. The later phase of motor skill learning may primarily involve feedback-independent mechanisms operating under the classic Hebbian rule. With these changes under distinct constraints and mechanisms, sensorimotor learning establishes dedicated circuitry for the reproduction of stereotyped neural activity patterns and behavior.

Active cortical dendrites modulate perception

There is as yet no consensus concerning the neural basis of perception and how it operates at a mechanistic level. We found that Ca²⁺ activity in the apical dendrites of a subset of layer 5 (L5) pyramidal neurons in primary somatosensory cortex (S1) in mice is correlated with the threshold for perceptual detection of whisker deflections. Manipulating the activity of apical dendrites shifted the perceptual threshold, demonstrating that an active dendritic mechanism is causally linked to perceptual detection.

Functional Organization of Flash-Induced V1 Offline Reactivation

The primary visual cortex exhibits a late, long response with a latency of >300 ms and an immediate early response that occurs ∼100 ms after a visual stimulus. The late response is thought to contribute to visual functions such as sensory perception, iconic memory, working memory, and forming connections between temporally separated stimuli. However, how the visual late response is generated and organized is not completely understood. In the mouse primary visual cortex in vivo, we isolated long-delayed responses by using a brief light-flash stimulus for which the stimulus late response occurred long after the stimulus offset and was not contaminated by the instantaneous response evoked by the stimulus. Using whole-cell patch-clamp recordings, we demonstrated that the late rebound response was shaped by a net-balanced increase in excitatory and inhibitory synaptic conductances, whereas transient imbalances were caused by intermittent inhibitory barrage. In contrast to the common assumption that the neocortical late response reflects a feedback signal from the downstream higher-order cortical areas, our pharmacological and optogenetic analyses demonstrated that the late responses likely have a thalamic origin. Therefore, the late component of a sensory-evoked cortical response should be interpreted with caution.

SIGNIFICANCE STATEMENT

The long-delayed responses of neocortical neurons are thought to arise from cortical feedback activity that is related to sensory perception and cognition. The mechanism of neocortical late responses was investigated using multiple electrophysiological techniques and the findings indicate that it actually arises from the thalamus. In addition, during the late response, excitation and inhibition are balanced, but inhibition is dominant in patterning action potentials.

Voltage-sensitive dye imaging of mouse neocortex during a whisker detection task

Sensorimotor processing occurs in a highly distributed manner in the mammalian neocortex. The spatiotemporal dynamics of electrical activity in the dorsal mouse neocortex can be imaged using voltage-sensitive dyes (VSDs) with near-millisecond temporal resolution and [Formula: see text] spatial resolution. Here, we trained mice to lick a water reward spout after a 1-ms deflection of the C2 whisker, and we imaged cortical dynamics during task execution with VSD RH1691. Responses to whisker deflection were highly dynamic and spatially highly distributed, exhibiting high variability from trial to trial in amplitude and spatiotemporal dynamics. We differentiated trials based on licking and whisking behavior. Hit trials, in which the mouse licked after the whisker stimulus, were accompanied by overall greater depolarization compared to miss trials, with the strongest hit versus miss differences being found in frontal cortex. Prestimulus whisking decreased behavioral performance by increasing the fraction of miss trials, and these miss trials had attenuated cortical sensorimotor responses. Our data suggest that the spatiotemporal dynamics of depolarization in mouse sensorimotor cortex evoked by a single brief whisker deflection are subject to important behavioral modulation during the execution of a simple, learned, goal-directed sensorimotor transformation.

Parallel pathways from whisker and visual sensory cortices to distinct frontal regions of mouse neocortex

The spatial organization of mouse frontal cortex is poorly understood. Here, we used voltage-sensitive dye to image electrical activity in the dorsal cortex of awake head-restrained mice. Whisker-deflection evoked the earliest sensory response in a localized region of primary somatosensory cortex and visual stimulation evoked the earliest responses in a localized region of primary visual cortex. Over the next milliseconds, the initial sensory response spread within the respective primary sensory cortex and into the surrounding higher order sensory cortices. In addition, secondary hotspots in the frontal cortex were evoked by whisker and visual stimulation, with the frontal hotspot for whisker deflection being more anterior and lateral compared to the frontal hotspot evoked by visual stimulation. Investigating axonal projections, we found that the somatosensory whisker cortex and the visual cortex directly innervated frontal cortex, with visual cortex axons innervating a region medial and posterior to the innervation from somatosensory cortex, consistent with the location of sensory responses in frontal cortex. In turn, the axonal outputs of these two frontal cortical areas innervate distinct regions of striatum, superior colliculus, and brainstem. Sensory input, therefore, appears to map onto modality-specific regions of frontal cortex, perhaps participating in distinct sensorimotor transformations, and directing distinct motor outputs.

Transformation of Perception from Sensory to Motor Cortex

To better understand how a stream of sensory data is transformed into a percept, we examined neuronal activity in vibrissal sensory cortex, vS1, together with vibrissal motor cortex, vM1 (a frontal cortex target of vS1), while rats compared the intensity of two vibrations separated by an interstimulus delay. Vibrations were "noisy," constructed by stringing together over time a sequence of velocity values sampled from a normal distribution; each vibration's mean speed was proportional to the width of the normal distribution. Durations of both stimulus 1 and stimulus 2 could vary from 100 to 600 ms. Psychometric curves reveal that rats overestimated the longer-duration stimulus-thus, perceived intensity of a vibration grew over the course of hundreds of milliseconds even while the sensory input remained, on average, stationary. Human subjects demonstrated the identical perceptual phenomenon, indicating that the underlying mechanisms of temporal integration generalize across species. The time dependence of the percept allowed us to ask to what extent neurons encoded the ongoing stimulus stream versus the animal's percept. We demonstrate that vS1 firing correlated with the local features of the vibration, whereas vM1 firing correlated with the percept: the final vM1 population state varied, as did the rat's behavior, according to both stimulus speed and stimulus duration. Moreover, vM1 populations appeared to participate in the trace of the percept of stimulus 1 as the rat awaited stimulus 2. In conclusion, the transformation of sensory data into the percept appears to involve the integration and storage of vS1 signals by vM1.

From single cells and single columns to cortical networks: dendritic excitability, coincidence detection and synaptic transmission in brain slices and brains

Although patch pipettes were initially designed to record extracellularly the elementary current events from muscle and neuron membranes, the whole-cell and loose cell-attached recording configurations proved to be useful tools for examination of signalling within and between nerve cells. In this Paton Prize Lecture, I will initially summarize work on electrical signalling within single neurons, describing communication between the dendritic compartments, soma and nerve terminals via forward- and backward-propagating action potentials. The newly discovered dendritic excitability endows neurons with the capacity for coincidence detection of spatially separated subthreshold inputs. When these are occurring during a time window of tens of milliseconds, this information is broadcast to other cells by the initiation of bursts of action potentials (AP bursts). The occurrence of AP bursts critically impacts signalling between neurons that are controlled by target-cell-specific transmitter release mechanisms at downstream synapses even in different terminals of the same neuron. This can, in turn, induce mechanisms that underly synaptic plasticity when AP bursts occur within a short time window, both presynaptically in terminals and postsynaptically in dendrites. A fundamental question that arises from these findings is: 'what are the possible functions of active dendritic excitability with respect to network dynamics in the intact cortex of behaving animals?' To answer this question, I highlight in this review the functional and anatomical architectures of an average cortical column in the vibrissal (whisker) field of the somatosensory cortex (vS1), with an emphasis on the functions of layer 5 thick-tufted cells (L5tt) embedded in this structure. Sensory-evoked synaptic and action potential responses of these major cortical output neurons are compared with responses in the afferent pathway, viz. the neurons in primary somatosensory thalamus and in one of their efferent targets, the secondary somatosensory thalamus. Coincidence-detection mechanisms appear to be implemented in vivo as judged from the occurrence of AP bursts. Three-dimensional reconstructions of anatomical projections suggest that inputs of several combinations of thalamocortical projections and intra- and transcolumnar connections, specifically those from infragranular layers, could trigger active dendritic mechanisms that generate AP bursts. Finally, recordings from target cells of a column reveal the importance of AP bursts for signal transfer to these cells. The observations lead to the hypothesis that in vS1 cortex, the sensory afferent sensory code is transformed, at least in part, from a rate to an interval (burst) code that broadcasts the occurrence of whisker touch to different targets of L5tt cells. In addition, the occurrence of pre- and postsynaptic AP bursts may, in the long run, alter touch representation in cortex.

Feedback Synthesizes Neural Codes for Motion

In senses as diverse as vision, hearing, touch, and the electrosense, sensory neurons receive bottom-up input from the environment, as well as top-down input from feedback loops involving higher brain regions [1-4]. Through connectivity with local inhibitory interneurons, these feedback loops can exert both positive and negative control over fundamental aspects of neural coding, including bursting [5, 6] and synchronous population activity [7, 8]. Here we show that a prominent midbrain feedback loop synthesizes a neural code for motion reversal in the hindbrain electrosensory ON- and OFF-type pyramidal cells. This top-down mechanism generates an accurate bidirectional encoding of object position, despite the inability of the electrosensory afferents to generate a consistent bottom-up representation [9, 10]. The net positive activity of this midbrain feedback is additionally regulated through a hindbrain feedback loop, which reduces stimulus-induced bursting and also dampens the ON and OFF cell responses to interfering sensory input [11]. We demonstrate that synthesis of motion representations and cancellation of distracting signals are mediated simultaneously by feedback, satisfying an accepted definition of spatial attention [12]. The balance of excitatory and inhibitory feedback establishes a "focal" distance for optimized neural coding, whose connection to a classic motion-tracking behavior provides new insight into the computational roles of feedback and active dendrites in spatial localization [13, 14].

Multisensory integration in C. elegans

Multisensory integration is a neural process by which signals from two or more distinct sensory channels are simultaneously processed to form a more coherent representation of the environment. Multisensory integration, especially when combined with a survey of internal states, provides selective advantages for animals navigating complex environments. Despite appreciation of the importance of multisensory integration in behavior, the underlying molecular and cellular mechanisms remain poorly understood. Recent work looking at how Caenorhabditis elegans makes multisensory decisions has yielded mechanistic insights into how a relatively simple and well-defined nervous system employs circuit motifs of defined features, synaptic signals and extrasynaptic neurotransmission, as well as neuromodulators in processing and integrating multiple sensory inputs to generate flexible and adaptive behavioral outputs.

The Cortical Processing of Sensorimotor Sequences is Disrupted in Writer's Cramp

Evidence for pre-existing abnormalities in the sensory and motor systems has been previously reported in writer's cramp (WC). However, the processing of somatosensory information during motor planning has received little attention. We hypothesized that sensorimotor integration processes might be impaired partly due to a disruption in the parieto-premotor network. To test this assumption, we designed 2 nonwriting motor tasks in which subjects had to perform a 4-finger motor sequence either on the basis of sensory stimuli previously memorized (SM task) or freely generated (SG task). Brain activity was measured by combining event-related functional magnetic resonance imaging and coherency electroencephalography in 15 WC patients and 15 normal controls. The bold signal was decreased in patients in both tasks during sensory stimulation but not during movement execution. However, the EEG study showed that coherency was decreased in patients compared with controls, during the delay of the SM task and during the execution of the SG task, on both the whole network and for specific couples of electrodes. Overall, these results demonstrate an endophenotypic impairment in the synchronization of cortical areas within the parieto-premotor network during somatosensory processing and motor planning in WC patients.

The importance of constructive feedback: Implications of top-down regulation in the development of neural circuits

Neural circuits in sensory pathways develop through a general strategy of overproduction of synapses followed by activity-driven pruning to fine-tune connectivity for optimal function. The early visual pathway, consisting of the retina → visual thalamus → primary visual cortex, has served for decades as a powerful model system for probing the mechanisms and logic of this process. In addition to these feedforward projections, the early visual pathway also includes a substantial feedback component in the form of corticothalamic projections from the deepest layer of primary visual cortex. The role of this feedback in visual processing has been studied extensively in mature animals, yet historically, its role in development has received comparatively little attention. Recent technological advances allowing for selective manipulation of neural activity in development led to the uncovering of a role for feedback in guiding the refinement of the forward projection from retina to visual thalamus. Here we discuss the implications of feedback exerting influence on the development of sensory pathways. We propose several possible advantages to constructing neural circuits with top-down regulation, and discuss the potential significance of this finding for certain neurologic disorders.

Segregated fronto-cortical and midbrain connections in the mouse and their relation to approach and avoidance orienting behaviors

The orchestration of orienting behaviors requires the interaction of many cortical and subcortical areas, for example the superior colliculus (SC), as well as prefrontal areas responsible for top–down control. Orienting involves different behaviors, such as approach and avoidance. In the rat, these behaviors are at least partially mapped onto different SC subdomains, the lateral (SCl) and medial (SCm), respectively. To delineate the circuitry involved in the two types of orienting behavior in mice, we injected retrograde tracer into the intermediate and deep layers of the SCm and SCl, and thereby determined the main input structures to these subdomains. Overall the SCm receives larger numbers of afferents compared to the SCl. The prefrontal cingulate area (Cg), visual, oculomotor, and auditory areas provide strong input to the SCm, while prefrontal motor area 2 (M2), and somatosensory areas provide strong input to the SCl. The prefrontal areas Cg and M2 in turn connect to different cortical and subcortical areas, as determined by anterograde tract tracing. Even though connectivity pattern often overlap, our labeling approaches identified segregated neural circuits involving SCm, Cg, secondary visual cortices, auditory areas, and the dysgranular retrospenial cortex likely to be involved in avoidance behaviors. Conversely, SCl, M2, somatosensory cortex, and the granular retrospenial cortex comprise a network likely involved in approach/appetitive behaviors.

Secondary Motor Cortex: Where 'Sensory' Meets 'Motor' in the Rodent Frontal Cortex

In rodents, the medial aspect of the secondary motor cortex (M2) is known by other names, including medial agranular cortex (AGm), medial precentral cortex (PrCm), and frontal orienting field (FOF). As a subdivision of the medial prefrontal cortex (mPFC), M2 can be defined by a distinct set of afferent and efferent connections, microstimulation responses, and lesion outcomes. However, the behavioral role of M2 remains mysterious. Here, we focus on evidence from rodent studies, highlighting recent findings of early and context-dependent choice-related activity in M2 during voluntary behavior. Based on the current understanding, we suggest that a major function for M2 is to flexibly map antecedent signals such as sensory cues to motor actions, thereby enabling adaptive choice behavior.